The noise-reduction potential of Radar Vegetation Index for crop management in the Czech Republic-Reference-Cited by-同舟云学术

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The noise-reduction potential of Radar Vegetation Index for crop management in the Czech Republic

Published:2021-09-04 Issue: Volume: Page:
ISSN:1385-2256
Container-title:Precision Agriculture
language:en
Short-container-title:Precision Agric

Author:

Tůma Lukáš,Kumhálová Jitka,Kumhála František^ORCID,Krepl Vladimír

Funder

Česká Zemědělská Univerzita v Praze

česká zemědělská univerzita v praze

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences

Link

https://link.springer.com/content/pdf/10.1007/s11119-021-09844-5.pdf

Reference77 articles.

1. Atzberger, C. (2013). Advances in remote sensing of agriculture: Context description, existing operational monitoring systems and major information needs. Remote Sensing, 5, 949–981. https://doi.org/10.3390/rs5020949

2. Abdikan, S., Sekertekin, A., Ustunern, M., Balik Sanli, F., & Nasirzadehdizaji, R. (2018). Backscatter analysis using multi-temporal Sentinel 1 SAR data for crop growth of maize in Konya Basin, Turkey. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-3, Proceedings of the ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing”, Beijing, China, 7–10 May 2018; 9–13. https://doi.org/10.5194/isprs-archives-XLII-3-9-2018

3. Bégué, A., Todoroff, P., & Pater, J. (2008). Multi-time scale analysis of sugarcane within-field variability: Improved crop diagnosis using satellite time series? Precision Agriculture, 9, 161–171. https://doi.org/10.1007/s11119-008-9063-3.

4. Bhandaria, A. K., Kumara, A., & Singhb, G. K. (2012). Feature extraction using normalized difference vegetation index (NDVI): A case study of Jabalpur City. Procedia Technology, 6, 612–621. https://doi.org/10.1016/j.protcy.2012.10.074

5. Badr, G., Hoogenboom, G., Davenport, J., & Smithyman, J. (2015). Estimating growing season length using vegetation indices based on remote sensing: A case study for vineyards in Washington State. Transactions of the ASABE, 58, 551–564. https://doi.org/10.13031/trans.58.10845

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